Abstract
The rebound index Cr is an important design parameter in engineering construction, and its determination is cumbersome and susceptible to errors. Explaining the macroscopic rebound characteristic parameter Cr from the perspective of microscopic mechanism is an important research area that is addressed in this study. In this paper, the different soil parameters, including the Cr parameter and the physical parameters (void ratio er liquid limit water content WL, and plasticity index Ip), have been determined through experiments for the undisturbed clay of Chongming East Shoal (CES), Shanghai. Further, scanning electron microscopy (SEM) imaging was used to analyze the microstructural features. Through SEM, the grey correlation degree, the average abundance of structural units ACp and the average equivalent diameter of pores ADv were determined as the soil microstructure parameters with the most significant correlation with Cr. The predictive analysis model of Cr was then carried out combined with the PSO-SVM algorithm. In order to evaluate the influence of microscopic parameters of soil on the prediction accuracy, four sets of input parameter combinations were used. The results indicate the high prediction accuracy of the developed model. Sensitivity analysis was also carried out, which showed that the sensitivity of Cr to ACp and ADv was significantly lower than e; however, the difference from wL and Ip was small, indicating that it is imperative to consider microscopic parameters while predicting Cr. This study, thus, provides a basis and method for predicting the rebound index of soil from the microstructure perspective.
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Abbreviations
- AC :
-
Average abundance
- AC p :
-
Average abundance of structural units
- AC v :
-
Average abundance of pores
- AD :
-
Average equivalent diameter
- AD p :
-
Average equivalent diameter of structural units
- AD v :
-
Average equivalent diameter of pores
- AF :
-
Average shape factor
- AF p :
-
Average shape factor of structural units
- AF v :
-
Average shape factor of pores
- AR :
-
Average roundness
- AR P :
-
Average roundness of structural units
- AR v :
-
Average roundness of pores
- B :
-
The length of the short axis
- C :
-
Abundance (see Fig. 3)
- C :
-
The penalty factor (see Fig. 6)
- C C :
-
Compression index
- C r :
-
Rebound index
- D :
-
Equivalent diameter
- e :
-
Void ratio
- F :
-
Fhape factor
- g :
-
The kernel parameter
- G best :
-
The best fitness value of the group
- I p :
-
Plasticity index
- k :
-
Slope of the rebound curve in the isotropic consolidation test
- L :
-
The length of the long axis
- MAE:
-
Mean absolute error
- P :
-
Pressures
- P best :
-
The best fitness value of an individual
- R :
-
Roundness
- R2 :
-
Coefficient of determination
- RMSE:
-
Root mean square error
- w :
-
Water content
- w L :
-
Liquid limit water content
- w P :
-
Plastic limit water content
- ρ :
-
Natural density
- ρ d :
-
Dry bulk density
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Acknowledgments
This research was funded by the Key Laboratory of Land Subsidence Monitoring and Prevention of the Ministry of Natural Resources (Grant No. KLLSMP201801; No. 2019(D)-004(F)-01; No. 2020(D)-011(F)-03); National Natural Science Foundation of China International (Regional) Cooperation and Exchange Key Project (Grant No. 41820104001); National Key Research and Development Plan (Grant No. 2018YFC1505301; No. 2018YFC1505304).
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Dong, J., Wang, B., Yan, X. et al. Prediction of Undisturbed Clay Rebound Index Based on Soil Microstructure Parameters and PSO-SVM Model. KSCE J Civ Eng 26, 2097–2111 (2022). https://doi.org/10.1007/s12205-022-1031-3
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DOI: https://doi.org/10.1007/s12205-022-1031-3